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Poster Introduction
Winchester 2016
Technological advances in
habitat mapping
Winchester 2016
#1
Marine Geobigdata Processing and Seabed
Characterisation Using IQmulus European Platform
Touria Bajjouk on behalf IQmulus project team
Aims at the development of an infrastructure and platform for
the integration, fusion, processing and visualization of very
large and highly heterogeneous spatial data sets that will
support decision-making processing.
LAND
URBAN
MARINE
IQmulus Marine Showcases Functionalities
©SeaZone
Bathymetric Data
Deconfliction
Http://www.iqmulus.eu
DEM Generation and
Change Detection
Lidar Full Waveform
Processing
#2
Joana Gafeira, Diego Diaz-Doce and David Long
Innangi S.(*), Tonielli R.(*), Bonanno A(**), Innangi M.(°)
(*) Istituto per l’Ambiente Marino Costiero, IAMC-CNR Sede, Napoli, Italy
(**) Istituto per l’Ambiente Marino Costiero, IAMC-CNR UO Capo Granitola, TorrettaGranitola, Mazara, Italy
(°) Dipartimento di Scienze e Tecnologie Ambientali, Biologiche e Farmaceutiche,
Seconda Università di Napoli, Caserta, Italy.
#4
Hanging Gardens: Vertical walls from images
to fine-scale 3D reconstruction
Katleen Robert, Veerle Huvenne, Claudio Lo Iacono, Russell Wynn, Leigh Marsh and Aggeliki Georgiopoulou
Photogrammetry (Structure from Motion)
Forward mounted ROV MBES
SfM 3D Reconstruction – Rockall Bank
#5
Quantitative analysis of mini-mounds from the Explorer
and Dangeard canyons area: an automated approach
Explorer
Province
Dangeard
Province
•
•
• An ArcGIS Tool Box created (BGS Seabed
Mapping Tool). Used to recognise, delineate
and characterise morphometrically sea-bed
mounds.
• Time-efficient approach provides unbiased and
accurate mapping methodology and enables
quantitative analyses of potentially vast
numbers of features.
818 mounds mapped in Explorer
province.
2044 mounds mapped in
Joana Gafeira [email protected]
Dangeard province.
Heather Stewart [email protected]
Coastal and shallow water
habitats
Winchester 2016
#7
Variation in Rocky Reef Habitat
in California State Waters
Guy R. Cochrane
About a fourth of the California Seafloor Mapping
Program data has been analyzed and published.
We can now compare habitat in diverse areas of the
California mainland waters.
The area of rocky reef habitat in Northern California,
is over an order of magnitude greater than the area
of rocky reef in the Santa Barbara area of Southern
California.
This is likely due to the local tectonics and wave
energy.
Strike slip tectonics control the structure of the
Northern California waters whereas in the Santa
Barbara area the tectonics are compressive.
Wave energy is higher along the Northern California
coast
Black Bream Nest Identification – A Habitat Mapping Case Study
#8
11
Sam Drawbridge
www.fugro.com
#9
James Duffy
Drones &
cameras
Submerged
aquatic
vegetation &
turtles
Benthic habitat mapping for the nearshore ecological monitoring of Dokdo (Dok island) in
the East Sea (Sea of Japan)
Dr. Chang Hwan Kim
Detailed bathymetry + Sonar Image
#13
Benthic habitat Seabed condition analysis
Detailed bathymetry + Underwater Camera Image
Analysis for monitoring of the population of sea
urchin and macroalgae based on seabed image
Quantitative and Effective
Benthic habitat mapping for the
nearshore ecological monitoring
High-resolution underwater composite photograph image maps are draped on the detailed bathymetry
#14
#16
Seafloor mapping of Frobisher Bay,
Baffin Island, Canadian Arctic Archipelago
Brian J. Todd1, John Shaw1, D. Calvin Campbell1 and David J. Mate2
1. Geological Survey of Canada (Atlantic), P.O. Box 1006, Dartmouth, Nova Scotia, Canada B2Y 4A2
2. Canadian Northern Economic Development Agency, P.O. Box 40, Iqaluit, Nunavut, Canada X0A 0H0
• Logistically challenging to survey/sample in this
macrotidal Arctic environment
• Rugged and rocky seafloor shaped by ice streams in
the last glacial period
Shelf and deep-sea habitats
Winchester 2016
#17
Spatial Transferability of Species
Distribution Models in the Deep Sea
#18
Chloe Game
• Species distribution modelling is an important and recurring tool in conservation of
deep sea habitats and resource management.
• The ability of these models to accurately predict species occurrence outside of the model
calibration region is less studied
• Focus on vulnerable marine ecosystems including cold-water coral reefs, sponge
grounds and xenophyophores
Lophelia pertusa reef summit
Stylasterid corals and lobose sponges
Xenophyophore, Syringammina fragellisima
Object Based Image Analysis of bioclastic mounds for ecosystembased ocean management
#19
A. Jarna1 , N.J. Baeten1, T. Thorsnes1, L. Bjarnadottir1, M. Dolan1, M. Diesing2
1
DATA
Study area (2) Sula Reef
Geological Survey of Norway (NGU), 2 Centre for Environment Fisheries and Aquaculture Science (CEFAS)
[email protected]
CLASSIFICATION
Study areas:
•Aktivneset area (1)
•Sula Reef (2)
2
1
Bathymery
Backscatter
EXPORT
BPI10
Curvature
BPI20
Smooted polygons .shp
Slope
0
1
2 km
#20
#21
Fine Scale Mapping and The Edge Effect:
Distributions of Benthic Fauna in an Antarctic
Hydrothermal Vent Field
Virginia Russell
-
 Does the Edge Effect occur at
Hydrothermal Vents?
-
 What are the key environmental
factors that determine distributions
of fauna?
-
 What implications does this have
on future
exploitation of vents?
-
#22
The role of food input in shaping biodiversity patterns in
benthic seamount habitats across the Equatorial Atlantic
Lissette Victorero, Sian Henley, Michelle Taylor, Laura Robinson , Jon Copley and Veerle Huvenne
• Seamounts
• Particulate Organic
Carbon
Food input
• How to incorporate food input into benthic
spatial habitat models?
#24
National mapping program
management and data-sharing
Winchester 2016
Harmonising sediment mapping on the Norwegian Shelf Challenges and some solutions
#25
Valérie Bellec*, Nicole Baeten*, Heidi Olsen*, Liv Plassen*, Dag Ottesen*,
Margaret Dolan*, Lilja Rún Bjarnadóttir*, Reidulv Bøe*, Aave Lepland*, Terje Thorsnes*
* Geological Survey of Norway (NGU), Trondheim. [email protected]
Some challenges and solutions:
1- Different multibeam (MBB) and single beams systems
(mostly Em1002, EM300/302, EM710, EM2040 and Olex
single beam),
Good understanding of MBB systems, learn how
seafloor geomorphology gives indications about grain-size.
EM710
2- Different interpreters at different years: presently 5
interpreters mapping adjacent areas,
Semi-automatic classifications such as object-based and
angular response analysis to produce more objective
maps.
3- Use of MBB with lower quality (different origins:
industry, hydrographic services), and delay between
multibeam acquisition and ground-truthing (up to 20
years),
Ground-truthing closer to MBB acquisition, understand
sediment dynamic.
OlexSingle beam
EM710
#26
Compiling data on seabed substrates and
sedimentation rates from Europe - EMODnet
Kaskela, Kotilainen, Alanen,
Stevenson & EMODnet Geology partners:
Geology
The EMODnet -Geology project has collected and combined geological
information at a scale of 1:250000 from all European sea areas.
Here we will present some of the outputs of the project: the combined
seabed substrate data and the sedimentation rate data.
#27
#28
#30
genesis
Guideline for standardized seafloor mapping
in the German Exclusive Economic Zone (EEZ)
Claudia Propp et al.
How to create a realistic map of the heterogenous seafloor?
Bring most information possible into one map!
It should be reproducible!?
Do it in a standardized way!
see our
guideline
#31
Alan Stevenson (British Geological Survey) and many others.
The integration of seabed mapping information in the UK, Europe and recent
trans-Atlantic collaboration.
• UK Marine Environmental Mapping
Programme (MAREMAP);
• European Marine Observation and Data
Network (EMODnet);
• Towards an Atlantic seabed mapping strategy
(Atlantic Ocean Research Alliance)
– Leveraging existing ocean exploration knowledge,
infrastructure and programmes
Methods for creating a broad-scale map
of seabed habitats
Mickaël Vasquez, on behalf of the EMODnet Seabed habitats consortium
Central to EMODnet Seabed habitats is the
production of a broad-scale map of seabed habitats
for all the European basins.
A broad-scale seabed habitat map typically describes the
environmental conditions that occur at the seabed that are
known to influence the distribution of plant and/or animal
communities .
The poster illustrates the method using the example of the
Black Sea
#32
A broad-scale habitat map is, in its basic form, a combination of
two key categorical layers: seabed substrate types and biological
zones. In the Black Sea, an additional categorical layer also comes
into play: the oxygen regimes.
The seabed substrate layer is provided by EMODnet Geology. The biological zone and oxygen regime layers are produced by overlaying
oceanography data layers that are compiled from fundamental physical parameters in the basin (i.e. bathymetry, light, temperature, and
density). The entire workflow is carried out with the use of Geographical Information System (GIS) techniques.
#33
Anthropogenic and natural
disturbance effects on marine habitats
Winchester 2016
#34
#34
Predictive models of Vulnerable
Marine Ecosystem (VME) indicator
species biomass distribution –
including the effects of fishing
activity
Potential
biomass
Current
Anna-Leena Downie et al.
Fishin
g
Relative
Biomass
Without Fishing
ASSESSMENT
Mean
curren
t
2000
Predicted…
PREDICTION
%
Clay
Random
Forest
model
1500
1000
500
0
Clos
ed
Fish
ed
Othe
r
Sponges…
#38
Disturbance in the deep:
a model for ecological
succession in the deep
sea
Leigh Marsh , Steve Carey , Peter Talling
1,3
1 University
2
3
of Southampton 2 Ocean Exploration Trust 3 National
Oceanography Centre, Southampton
Using Vessel Monitoring System (VMS) data
to investigate pressure-state relationships in
offshore MPAs
Tammy Noble-James
• JNCC & Cefas have used gridded
pressure layers to investigate effects of
abrasion on benthic assemblages.
• This poster presents key results from studies
conducted at two offshore MPAs:
- Dogger Bank Site of Community
Importance
#39
- Central Fladen Nature Conservation MPA
© JNCC & Cefas
Role of oceanography in habitat
mapping
Winchester 2016
Deep-sea habitats and dense shelfwater formation:
#40
a fragile climate-dependent relation studied from
geomorphological signatures
David Amblas, Scott Polar Research Institute – Univ. of Cambridge, UK
([email protected])
Miquel Canals, CRG Marine Geosciences – Univ. of Barcelona, Spain
Julian A. Dowdeswell, Scott Polar Research Institute – Univ. of
Cambridge, UK
Anna Sanchez-Vidal, CRG Marine Geosciences – Univ. of Barcelona,
Spain
Ricardo Silva Jacinto, Lab. Environnements Sédimentaires – IFREMER,
France
This project has received funding from the European Union’s Horizon
2020 research and innovation programme under the Marie
Sklodowska-Curie grant agreement No 658358
#41
Cold-water coral ecosystems in Cassidaigne Canyon:
an assessment of their potential distribution
Marie-Claire Fabri , Annaelle Bargain , Ivane Pairaud , Laura Pedel
Where: South of France
Environmental living conditions :
Terrain parameters
Species:
Cold-water coral Madrepora oculata
Habitat
Suitability
Models
-ENFA
-MaxEnt
-GLM
Hydrodynamic parameters
Predictive habitat modeling of Cold Water Coral Distribution in the Bari
Canyon (Adriatic Sea) with Hydrodynamic variables
#42
Federica Foglini, Annaëlle BARGAIN, Lorenzo Angeletti, Davide Bonaldo, Marco Taviani
EGVs Variables
CWC Occurences
Hydrodynamic
Variables
Model Output MAXENT
ENFA
GLM
Use of ADELIE-SIG
(Ifremer) on video
transects and
digital images
Development of standards for
classification, confidence and
assessment of habitat maps
Winchester 2016
#43
Quantitative prediction
of grain size
Interpolated
rasters
Low-coverage
MBES data
#44
#45
Comparison of Supervised and Unsupervised Benthic Habitat Classifications:
Case Study from the Belgian Continental Shelf
Montereale Gavazzi, G.,(1,2) Roche, M.,(4) Lurton, X.,(3) Van Lancker, V.,(1,2)
1, RBINS OD-Nature (Brussels, BE). 2, UGent-RCMG (Gent, BE).
3, IFREMER (Brest, FR). 4, FPS Economy (Brussels, BE)
1) – Supervised classification
2) – Comparison with unsupervised model
BHM Routine
Quantity & allocation
> Belgian State committed to > Seafloor
Integrity > Monitoring > Combination of
Trends and transitions
Acoustics and Ground Truth Data:

Study area
Ref.2

Ref.3
Ref.4
The areal extent and distribution of EUNIS
level 3 Habitats, as well as of the gravel
beds, remain within the margin of
uncertainty of the sediment distribution,
with reference to the Initial Assessment,
and
The ratio of the hard (‘gravel’) to fine
(‘sand’) substrate surface area must not
show a negative trend. Attention is
focussed here on Smothering, Abrasion
and Loss of habitats.
Overall
fS
mS+bio
cS+G
Difference
9.79
1.52
9.78
8.28
Allocation
9.37
1.1
9.47
8.16
Quantity
0.42
0.42
0.31
0.12
4) – Observed patterns?
3) – Change detection
MSFD
Differences/class
Preliminary results likely point to a
smothering process. Further monitoring is
important, since it is a major cause of
irreversible habitat loss, impeding
bentho-pelagic coupling, bio-encrustation
and ecological successional phases to
occur.
Dive 2008
ROV/2015
Mapping for Management and Conservation
of Marine Habitats.
Lough, N., Robinson, K., Ramsay, K. & Tavner, D.
• Brief introduction to NRW
• Two case studies (Seagrass mapping and UKHO Multibeam data)
• Reasons and the importance of marine mapping to NRW
#46
AN ILLUSTRATED GLOSSARY FOR EUROPEAN COLD-WATER CORAL HABITAT CHARACTERIZATION
1
2
Vertino A.V.1,3, Beuck L.2, Savini A. 1, Guillaumont B.4, Van den Beld I.4,
Corselli C.1, Freiwald A.3, Grehan A.5 & the CoralFISH members
3
4
5
#47
Ecosystem based management of corals, fish and fisheries
in the deep waters of Europe and beyond
Standardization of CWC habitat
classification and terminology
to enhance communication
(1) among scientists from different research fields
(geologists, biologists,oceanographers etc.)
(2) between scientists and decision makers
© ROV images: Belgica 09/14c RCMG (upper left), JAGO Team GEOMAR Kiel (upper right), M70-1_2006 MARUM (middle
left), Venture 2011 UCC (middle right, lower left) , Caracole IFREMER (lower right)
#48
• biotopes are imaginary
• species are hypotheses
• focusing on immediate legislative targets may
lead to poor science and adverse outcomes
• there is an opportunity to develop new
approaches to adequately address these
complex socio-scientific problems
#49
2016
Habitat mapping of VMEs along the inner shelf regions of the south-western Tyrrhenian
margin (southern Mediterranean ): a geo-statistical predictive approach.
Zizzo E.1, Sulli A.1, Agate M.1, Lo Iacono C.2
1
Department of Earth and Marine Sciences, University of Palermo, Via Archirafi 22, 90123 Palermo, Italy
2 National Oceanography Centre, European Way, SO14 3ZH Southampton, UK .
Predicted habitat mapping of
Posidonia oceanica
Predicted habitat mapping of
Cymodocea nodosa
Predicted habitat mapping of
Coralligenous
The Remote Coast: Baseline Mapping in Preparation for Arctic Coastal Disasters
After the event is too late
Integrated Remote Sensing Approach to
Address Baseline Mapping
51
www.fugro.com